1. Field of the Invention
The present invention relates generally to methods of and systems for Computer-Aided Diagnostic Mammography (CADM). In its more particular respects, it relates to automatic segmentation of digital mammograms into background, corresponding to the region external of the breast, and foreground, corresponding to the region within the breast, and automatic detection of a boundary contour or border between these regions as well as the detection of the nipple.
2. Description of the Related Art
Methods for segmentation and skinline detection are known from Nishikawa, R., et al, "Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms," SPIE 1905-46, February 1993 and from Yin, F. et al, "Computerized detection of masses in digital mammograms: Analysis of bilateral subtraction images," Medical Physics 18 (5), September/October 1991, both reflecting work at the University of Chicago and from Yabashi, S, et al. "Image Processing for recognition of tumor on mammography", Proceedings of the 1989 International Symposium on Noise and Clutter Rejection in Radars and Imaging Sensors.
Breast cancer is one of the primary causes of death for women in western societies. Because the vast majority of deaths due to cancer that originated in the breast could be prevented by early detection, national health organizations in the United States recommend that all women over the age of 50 have regular screening mammograms.
The reading or interpretation of screening mammograms is an art that requires extensive experience and attentiveness to detail. While the mammographer's primary sign for cancer is a mass visible on the mammogram, one of the more sensitive signs is the presence of small relatively bright spots (in film-screen mammography) corresponding to locally increased X-ray attenuation due to minute deposits of calcium salts known as microcalcifications, which are arranged in clusters. In fact, clustered micro-calcifications are often the only sign indicating an early in situ malignancy. However, identification of these clusters is difficult because they are frequently obscured by gradations in intensity produced by the surrounding tissue. Both the volume of mammograms to be interpreted and the difficulty of identifying the aforementioned and other not easily recognizable signs of malignancy motivate developments in Computer-Aided Diagnosis of Mammograms (CADM) to at least automatically mark or enhance features of interest, including suspect areas, in images displayed on a monitor for interpretation by the mammographer.
Digital mammograms suitable for computer-aided diagnosis may be obtained by scanning film taken by conventional X-ray mammography or by utilizing other X-ray detector types that produce electronic image signals that may be directly digitized without the necessity of producing a film intermediate. These detector types include X-ray image intensifier/camera chain, photostimuable phosphor plate/laser readout (see U.S. Pat. No. 4,236,078), and selenium plate/electrometer readout technologies. Such technologies are progressing in their spatial resolution and contrast sensitivities achieved and the latter two, particularly, may soon find widespread use for mammographic applications.
One of the early steps in a CADH system is to segment the image into foreground (corresponding to the breast) and background (corresponding to the external surround of the breast). This segmentation reduces the amount of further processing because extraneous pixels belonging to the background, which may be as many as two thirds of the pixels in the image, are removed from further consideration. The segmentation also produces information from which the boundary contour or border between the foreground and the background, theoretically at the skinline, could be ascertained. An understanding of how mammographers utilize the skinline in film-screen mammography today would be helpful at this point.
Mammographers review X-ray films of breasts taken from different views or projection directions. These include the head-to-toe viewing direction known as cranio-caudal (CC), the side-to-side viewing directions known as medio-lateral (ML) or lateral-medial (ML) and the viewing direction which is typically at a 45.degree. angle between head-to-toe and side-to-side known as oblique (OB). Due to the varying composition of the breast (a mixture of fat, parenchyma and stroma tissues) the contrast seen on mammograms varies tremendously across images. Often the skinline is not visible in one or all of these views. When a mammographer is not able to see the skinline on the viewing box, a special high intensity incandescent light, known as a hot light, is used to help locate the skin boundary and the subcutaneous region below it.
Locating the skinline is important to a mammographer in two respects. First, in and by themselves, skin conditions have diagnostic significance. Thickening in the skin and skin retractions are indications of malignancy. Conversely, microcalcifications found on, or immediately below the skinline are considered benign. Second, the skinline acts as a landmark. The locations of abnormalities, in many instances, are reported relative to the skinline, e.g. 2 cm. below the skinline. In addition, once a mammographer finds a suspicious lesion in one view, he must locate the same in another view. He does this by measuring the distance between the detected object and the skinline in one view and by looking for a similar object in the second image on an imaginary line the same distance away from the skinline. Finally, the mammographer has to assure that equal amounts of tissue, between skinline and chest wall, are visualized in all views taken. Routinely, the distance between a point on the skinline (typically the nipple if it can be detected visually) to the edge of the film in the direction of the chest wall is measured for all views. These distances should be approximately equal. If there are large discrepancies, the films are retaken.
Other uses of the skinline is as a registration aid in comparing images of the left and right breasts, or in comparing views of the same breast taken at different times, e.g. current and last previous studies. Lastly, the skinline can guide a visual search for the nipple, which like the skinline, is also a landmark. Unless the nipple is marked by a metal bead when the mammogram is taken, it is very difficult to detect. Often, it is not visualized in profile due to patient positioning or rolling over of the skin.
In the aforementioned publications reflecting work at the University of Chicago, the background is separated from foreground by an initial global threshold operation. This is followed by a morphological close operation to separate the gland from the noisy exterior. A tracking scheme using 4-point connectivity is used to trace the border. The border is smoothed using a running average of border coordinates. This is done independently for images of right and left sides. However, the smaller of the two detected borders is chosen and superimposed on both images for subsequent processing.
The problem with the aforementioned prior art methods is their exclusive reliance on a global threshold to accomplish the initial segmentation. One difficulty is in automatically selecting a meaningful threshold. Another difficulty is that whatever threshold is chosen, it may not consistently and reliably segment the mammogram because, due to noise and artifacts, the gray levels in the background and foreground can overlap and/or may necessitate manual cropping to eliminate background artifacts. Such manual cropping will become more difficult once American College of Radiology (ACR) labeling recommendations are adopted more widely. Further, it has been found that the boundary generated by this prior art method is likely to be at the dense parenchyma below the subcutaneous fatty region of the skin rather than the skinline itself. Since the subcutaneous fatty region could be as thick as 2.5 cm., the tissue erroneously labelled as background could be substantial.
In the Yabashi et al. publication, a one-dimensional gradient operation is applied to individual lines of data, and a threshold is applied to the determined unidirectional gradient generally normal to the chest wall to find the edge of the skin. Such an approach will not adequately segment the breast at points along the skinline where the normal to the skinline is significantly different from the normal to the chest wall.
Further, automatic detection of the nipple is not generally known. Such automatic detection could provide a reference point for visual or automatic correlation or registration of mammogram views of the same breast taken at different times or from different viewing directions or between mammogram views of the left and right breasts from the same viewing direction.